SAFE
EMTs extricate patients from wrecked cars, control bleeding, splint fractures, manage airways, and lift dead weight down stairwells — none of which any deployable robot does. The automatable slice is the paperwork tail: run reports, ePCR narratives, billing codes, dispatch triage prompts, and protocol lookup. Certification (NREMT plus state licensure) legally gates who may perform interventions and transport, and medical-direction protocols place accountability on a named human in the field.
Headcount grew steadily across the period.
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing.
BLS projection, 2024–2034
+5.1% 181,000 → 190,200 on the projections basis
Hard to automate, and growing
The work resists current AI and the BLS projects +5.1% more of these jobs by 2034. Note that safe does not mean well paid — several of the fastest-growing resistant occupations are among the lowest paid on the register.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~14,100 openings a year on average, including replacing people who leave.
EMT-PEMT-I/85EMT-I/99ParamedicDispatcherRescue WorkerMedical DriverFirst ResponderAmbulance DriverMedical TechnicianHealthcare SpecialistHealth Care SpecialistEmergency Medical DriverEmergency Room TechnicianEmergency Medical ResponderRescue Technician (Rescue Tech)Medical Equipment Delivery DriverEmergency Medical Technician (EMT)EMT-B (Emergency Medical Technician- Basic)Non-Emergency Medical Transportation DriverAdvanced Emergency Medical Technician (AEMT)Emergency Medical Technician - Basic (EMT-B)Emergency Department Technician (ED Technician)Onsite Medical Representative (Onsite Medical Rep)
Holding it up: embodiment . Weakest point: judgment & accountability .
Tasks largely resist digitisation Rolling a patient onto a longboard in a ditch, jaw-thrusting an unresponsive overdose, bagging while your partner drives, and deciding a stairchair won't fit the landing are tasks with no digital analogue — the 15 rather than 18 reflects that ePCR narratives, dispatch card triage, protocol lookup, and billing-code selection are genuinely being absorbed by software already sitting on the tablet you carry.
Hands-on in uncontrolled environments Every shift is uncontrolled terrain — highway shoulders in rain, third-floor walkups with no elevator, bathrooms too small to kneel in, combative patients, and 300-pound lifts done with two people — which is the definition of the top of the band rather than a case that needs arguing.
Licensed human required and personally liable NREMT certification plus state licensure legally gates who may perform interventions and transport, and your name on the run report ties you to the care given; it sits at 13 rather than 18 because you practice under a medical director's standing protocols rather than independent scope, so the physician's license absorbs a real share of the exposure.
Meaningful discretion Deciding trauma-center versus community ED, whether this chest pain is a load-and-go, when to stop working an arrest under termination-of-resuscitation criteria, and refusal-of-care capacity calls are real discretionary weight; the 13 rather than 17 is because protocols specify most of your decision tree and online medical control is a radio call away.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (15/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (13/20) is whether the law requires a licensed human to sign. Trust premium (15/20) is whether buyers specifically pay for a person. Judgment and accountability (13/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 41 of this occupation's 76 points (54%).
Embodiment (20/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 85/100, still SAFE.
Formal adoption of treat-no-transport / alternate-destination protocols under medical direction — where the EMT owns the disposition call (ED vs urgent care vs refusal) rather than transporting by default. CMS's ET3 model piloted exactly this; state reimbursement rules that pay for on-scene decision-making would make the ambiguous call the job's core rather than its edge.
Task-mix shift as the documentation tier is automated: if ePCR narrative, billing coding, and protocol lookup are absorbed by AI, the residual day is extrication, airway, hemorrhage control, and scene command under uncertainty — none of it automatable. This raises the score without any new law, but only because the automatable slice was already thin.
State EMS offices expanding scope-of-practice rules so that AI-generated dispatch triage or ePCR narratives require attestation by the licensed EMT on the run, with the license as the accountable signature — mirroring existing NREMT/state medical-direction attestation on drug administration. Also: state statutes (e.g. community paramedicine authorizing bills in ~20 states) that grant EMTs delegated authority for treat-and-refer decisions, each of which attaches personal licensure liability.
The limit. Embodiment is already maxed at 20 and cannot rise. The realistic ceiling is in the low-to-mid 80s: gains come almost entirely from scope-of-practice expansion (disposition authority, community paramedicine) converting EMTs from transport labor into accountable decision-makers. The countervailing risk is not automation but deskilling — if protocols become AI-driven checklists with medical direction reviewing remotely, judgment_accountability could fall instead.
| New York-Newark-Jersey City, NY-NJ | 13,780 | $53,820 +21% |
| Los Angeles-Long Beach-Anaheim, CA | 6,610 | $45,090 +1% |
| Chicago-Naperville-Elgin, IL-IN | 5,610 | $44,020 -1% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 4,970 | $47,790 +7% |
| San Francisco-Oakland-Fremont, CA | 3,580 | $51,480 +16% |
| Boston-Cambridge-Newton, MA-NH | 3,410 | $50,560 +14% |
| Atlanta-Sandy Springs-Roswell, GA | 3,090 | $47,500 +7% |
| Dallas-Fort Worth-Arlington, TX | 3,000 | $37,900 -15% |
| Lexington Park, MD | 80 | $68,160 +53% |
| Urban Honolulu, HI | 460 | $67,050 +51% |
| Redding, CA | 80 | $60,120 +35% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 76. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.